Client Report - Project 0: Introduction

Table of contents

• QUESTION|TASK 1
• QUESTION|TASK 2

import pandas as pd
import numpy as np
from lets_plot import *

LetsPlot.setup_html(isolated_frame=True)

# Learn morea about Code Cells: https://quarto.org/docs/reference/cells/cells-jupyter.html

# Include and execute your code here
from palmerpenguins import load_penguins
df = load_penguins()

QUESTION|TASK 1

Include the tables created from PY4DS: CH2 Data Visualization used to create the above chart (Hint: copy the code from 2.2.1. The penguins data frame and paste each in the cells below)

# Include and execute your code here
df

	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
0	Adelie	Torgersen	39.1	18.7	181.0	3750.0	male	2007
1	Adelie	Torgersen	39.5	17.4	186.0	3800.0	female	2007
2	Adelie	Torgersen	40.3	18.0	195.0	3250.0	female	2007
3	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN	2007
4	Adelie	Torgersen	36.7	19.3	193.0	3450.0	female	2007
...	...	...	...	...	...	...	...	...
339	Chinstrap	Dream	55.8	19.8	207.0	4000.0	male	2009
340	Chinstrap	Dream	43.5	18.1	202.0	3400.0	female	2009
341	Chinstrap	Dream	49.6	18.2	193.0	3775.0	male	2009
342	Chinstrap	Dream	50.8	19.0	210.0	4100.0	male	2009
343	Chinstrap	Dream	50.2	18.7	198.0	3775.0	female	2009

344 rows × 8 columns

A complete table showing all 344 penguins

include figures in chunks and discuss your findings in the figure.

# Include and execute your code here
df.head()

	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
0	Adelie	Torgersen	39.1	18.7	181.0	3750.0	male	2007
1	Adelie	Torgersen	39.5	17.4	186.0	3800.0	female	2007
2	Adelie	Torgersen	40.3	18.0	195.0	3250.0	female	2007
3	Adelie	Torgersen	NaN	NaN	NaN	NaN	NaN	2007
4	Adelie	Torgersen	36.7	19.3	193.0	3450.0	female	2007

5 samples of the initial dataset.

QUESTION|TASK 2

Recreate the example charts from PY4DS: CH2 Data Visualization of the textbook. (Hint: copy the chart code from 2.2.3. Creating a Plot, one for each cell below)

# Include and execute your code here
(
    ggplot(data=df, mapping=aes(x="flipper_length_mm", y="body_mass_g")) + geom_point()
)

Scatterplot showing the relation between flipper length and body mass.

include figures in chunks and discuss your findings in the figure.

# Include and execute your code here
(
    ggplot(
    data=df,
    mapping=aes(x="flipper_length_mm", y="body_mass_g", color="species"),
)
+ geom_point()
)

Separates the different species into different colors.

# Include and execute your code here
(
    ggplot(
    data=df,
    mapping=aes(x="flipper_length_mm", y="body_mass_g", color="species"),
)
+ geom_point()
+ geom_smooth(method="lm")
)

Added a smooth curve to further display the relationship between body mass and flipper length.

# Include and execute your code here
(
    ggplot(data=df, mapping=aes(x="flipper_length_mm", y="body_mass_g"))
    + geom_point(mapping=aes(color="species"))
    + geom_smooth(method="lm")
)

joined the separate lines into one

# Include and execute your code here
(
    ggplot(data=df, mapping=aes(x="flipper_length_mm", y="body_mass_g"))
    + geom_point(aes(color="species", shape="species"))
    + geom_smooth(method="lm")
    + labs(
        title="Body mass and flipper length",
        subtitle="Dimensions for Adelie, Chinstrap, and Gentoo Penguins",
        x="Flipper length (mm)",
        y="Body mass (g)",
        color="Species",
        shape="Species",
    )
)

Added different shapes for the species and improved labeling.